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Record W2333576263 · doi:10.2174/1386207311316040005

Ligand-Peroxidase Conjugates for Quantification of Receptor-Mediated Transport into Cells

2013· article· en· W2333576263 on OpenAlexaff
Jie Chen, Amandio Vieira

Bibliographic record

VenueCombinatorial Chemistry & High Throughput Screening · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiotin and Related Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEndocytosisBiotinylationInternalizationLigand (biochemistry)Transferrin receptorConjugateTransferrinReceptorChemistryCell biologyBiochemistryStreptavidinEndosomeBiologyBiotin

Abstract

fetched live from OpenAlex

Receptor-mediated cellular uptake of physiological regulators such as nutritional and hormonal factors represents a transport event with important consequences for cell differentiation, death, or proliferation. Although internalization pathways are important points of regulation, they have not been extensively explored as pharmacological targets in most cell types. An experimental strategy based on ligand-enzyme conjugates is presented in this report that may facilitate high-throughput screening for potent chemical modulators of the transport events. The method was tested on a human epidermoid cell line using a streptavidin-peroxidase conjugate, and human holo-transferrin as the model ligand, in a biotin-ligand conjugate. The proposed screening method is rapid, can be performed using multi-well plates, and involves small assay volumes. The modular nature of the ligand complex makes this method adaptable to the use of other biotinylated ligands, and the use of avidins conjugated to other enzymes. As is discussed, the method may also be applicable to other in vitro and in vivo transport assays. Keywords: Cell transport, epidermoid cells, ligand conjugates, receptor-mediated endocytosis, screening assay, Endocytosis, clathrin-mediated endocytosis, transferrin endocytosis, transferrin RME model, ligand-enzyme conjugate assay.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.232
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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